1. Technical Field of the Invention
The present invention relates in general to calibrating building energy simulations with performance data, and in particular, to a method and apparatus for applying corrective flows to better calibrate an audit building to the actual building.
2. Description of Related Art
Simulation tools to determine the energy performance of buildings aid in the analysis and design of energy-efficient buildings. When combined with performance data, simulation tools offer the possibility of evaluating, commissioning, diagnosing, optimally controlling, and identifying retrofit opportunities for buildings. Such simulations typically combine a description of the building and HVAC (Heating, Ventilating, and Air-Conditioning) systems with weather and occupancy-related data to calculate energy requirements. Because of the complexity of the computations, as well as input and output requirements, such simulations are usually implemented in the form of computer programs. Examples of such programs in the public domain are: BLAST (BLAST User's Manual 1986 is available from BLAST Support Office, University of Illinois, 1206 West Green Street, Urbana, Ill. 61801) and DOE-2 (DOE-2 Supplement (Version 2.1E/January 1994) is available from Lawrence Berkeley Laboratory, Energy and Environment Division, Berkeley, Calif. 94720).
Depending on the focus of the building analysis, restricted computations may be performed. For example, when the performance of the building shell is the focus, the simulations may be restricted to computing heating and cooling loads, without explicit consideration as to how these loads are met. (Heating and cooling loads refer to the amount of heat to be supplied or removed to provide specified space-conditioning; HVAC equipment operates by consuming electricity and/or gas and/or other energy source to satisfy this demand.) Time steps of one hour are common for these simulations, although selecting an hourly time step is only a matter of convenience. As noted above, several computer programs exist. Each differs in the manner in which it accounts for the complex details of the building, the related HVAC system, weather conditions, and occupancy characteristics; each program also differs in its input/output features. Some programs have been adopted as standard simulators in various projects.
Regardless of which of the several computer programs is utilized, when the simulated energy performance is compared with the measured energy performance, differences frequently exist. A variety of data may be used for comparison purposes. Such data includes fuel use (e.g., electricity), temperatures of various zones at an hourly or other interval, and consumption data recorded in utility bills. The data may be acquired by a variety of means such as from an existing energy management system in the building, from specially installed data loggers, from billing records, or any combination thereof. The data may be acquired, at least in part, by imposing conditions on the building deemed favorable to elicit certain building responses. Attempts may be made to reconcile the differences between simulated and measured performances by modifying the simulations in some manner to reduce the disagreement. Such a process is sometimes referred to as calibration or tuning of the simulations.
Because of the large number of inputs (often several hundred) to a simulation, attempts to directly modify the inputs to provide a best-fit have encountered serious difficulties. Using typically monitored data, it is not possible to calibrate the simulation by estimating the hundreds of inputs; therefore, approximations are necessary. Ad hoc adjustments of inputs, that are unfortunately not mathematically well-formulated, have been resorted to. A systematic method to perform a best fit on hourly data is an important need that remains unanswered by existing methodologies.
An approach called PSTAR was developed (Subbarao, K., "PSTAR-Primary and Secondary Terms Analysis and Renormalization" SERI/TR-254-3175 1988, which is available from Solar Energy Research Institute (now National Renewable Energy Laboratory), Golden, Colo.; see also "Short-Term Energy Monitoring for Commercial Buildings" by J. D. Balcomb, J. D. Burch, R. Westby, C. E. Hancock, and K. Subbarao, ACEEE 1994 Summer Study on Energy Efficiency in Buildings, American Council for an Energy Efficient Economy, Washington, D.C. 20036, Vol. 5, P. 1.) that modifies the heat flows in the energy balance instead of the direct inputs to the simulation. The various heat flows are calculated individually by combining the building characteristics obtained from a building audit with the measured driving functions.
Energy balance requires that they add up to zero for every hour or time step. However, due to differences between the audit building and the actual building, the heat flows do not usually add up to zero. Parameters are introduced to multiply (or "renormalize") the primary heat flows and are estimated from test data through a least squares fit to energy balance. (Introducing parameters associated with secondary terms and estimating them from data entails the danger of fitting on noise.) The test protocol as a way to elicit the parameters as well as heat flows to account for such features as phase shift of solar gains were introduced. To use the estimated parameters for predicting heating and cooling loads under different conditions (for example, to predict loads over a long-term period such as a year), a simplified program was developed. Furthermore, to convert heating and cooling loads to electrical and gas energy use requires simulation of systems and plants. Simple models with limited features were developed for this purpose. A software package called STEM (Short-Term Energy Monitoring) was developed to perform these computations (STEM-1.0 User Manual 1989, which is available from Solar Energy Research Institute (now National Renewable Energy Laboratory), Golden, Colo.).
The existing STEM package has three primary deficiencies. First, the STEM software performs explicit energy balance by disaggregating the heat flows that contribute to the energy balance and then computing all of them. This amounts to the development of a simulator. This is such a complex task that oversimplified models are used to compute some of these heat flows. (Some of the heat flows can be computed, at least in principle, from any simulator, such as DOE-2, by disabling certain features as discussed hereinbelow. With complex simulators, disabling certain features can result in unintended and undesirable effects, which in turn result in erroneous heat flows. In some situations, such disabling may be impossible.) A second STEM deficiency is that to incorporate the estimated parameters for determining long-term performance, such as annual energy use, many issues have to be addressed. Only limited capabilities are available, however. The third primary STEM deficiency is that only limited HVAC systems are modeled, and even so, their operation is oversimplified. These systems include pumps, fans, coils, control set-points, economizers, boilers, chillers, and humidifiers. Simulators such as DOE-2, on the other hand, accommodate a large number of systems and plants as well as various control options.
In other words, the features and simulation capabilities of STEM cannot compare to many commercial and public domain simulators already available. These commercial and public domain simulators have been developed over many years and at the expense of millions of dollars. Some are also carefully tailored to specific simulation tasks. Even attempting to develop a STEM-like program on par with these existing simulators would be a cost-prohibitive, unjustifiable expense. Furthermore, linking STEM with one of these existing programs is difficult to impossible and would provide only inadequate results. Hence, while several simulators have been developed at great effort with various user-communities as the target, a general method that results in a simulator of the user's choice that is calibrated to performance data remains an important need that is unanswered by existing computer programs and packages. In other words, the ability to use a powerful, extensive, well-documented, and thoroughly-tested simulator in conjunction with systematic and accurate calibration techniques has thus far eluded researchers. The present invention is directed to remedying this need as well as meeting the below-enumerated (and other) objects of the invention.